public UserClient GetUserInfo(String name, String pass)
{
UserClient answer = new UserClient();
UserDBDataSetWorkerTableAdapters.UserClientTableAdapter adapter = new UserDBDataSetWorkerTableAdapters.UserClientTableAdapter();
answer.SetID((int)adapter.GetUserID(name, pass));
answer.SetUsername(name);
answer.SetPass(pass);
return(answer);
}
public bool CheckCredentials(String UserName, String Password)
{
UserDBDataSetWorkerTableAdapters.UserClientTableAdapter checkAdapter = new UserDBDataSetWorkerTableAdapters.UserClientTableAdapter();
UserDBDataSetWorker.UserClientDataTable table = new UserDBDataSetWorker.UserClientDataTable();
checkAdapter.CheckCredentials(table, UserName, Password);
if (table.Count == 1)
{
return(true);
}
return(false);
}
private int GetUserClientID(String UserName, String Password)
{
UserDBDataSetWorkerTableAdapters.UserClientTableAdapter checkAdapter = new UserDBDataSetWorkerTableAdapters.UserClientTableAdapter();
UserDBDataSetWorker.UserClientDataTable table = new UserDBDataSetWorker.UserClientDataTable();
checkAdapter.CheckCredentials(table, UserName, Password);
if (table.Count == 1)
{
return(table[0].UserID);
}
return(-1);
}
public bool RegisterCredentials(String UserName, String Password)
{
bool answer = false;
if (!CheckCredentials(UserName, Password))//if username and password is not in the database already.
{
UserDBDataSetWorkerTableAdapters.UserClientTableAdapter adapter = new UserDBDataSetWorkerTableAdapters.UserClientTableAdapter();
adapter.UserClientInsert(UserName, Password);
answer = true;
}
return(answer);
}
/// <summary>
/// Add users on database to screen.
/// </summary>
public void Populate()
{
UserDBDataSetWorkerTableAdapters.UserClientTableAdapter adapter = new UserDBDataSetWorkerTableAdapters.UserClientTableAdapter();
UserDBDataSetWorker.UserClientDataTable userTable = adapter.GetUserWordCount();
allUsersLstView.Items.Clear();
foreach (UserDBDataSetWorker.UserClientRow row in userTable)
{
string[] subItems = new string[3];
subItems[0] = row.UserName;
subItems[1] = row.UserID.ToString();
subItems[2] = row.ItemArray[3].ToString();
allUsersLstView.Items.Add(new ListViewItem(subItems));
}
}
private void submitBtn_Click(object sender, EventArgs e)
{
bool passed = false;
if (parent.proctor.CheckCredentials(usernameRTxt.Text, passwordRTxt.Text))
{
UserDBDataSetWorkerTableAdapters.UserClientTableAdapter adapter = new UserDBDataSetWorkerTableAdapters.UserClientTableAdapter();
UserDBDataSetWorker.UserClientDataTable userTable = adapter.GetCheckCredentials(usernameRTxt.Text, passwordRTxt.Text);
parent.proctor.GetConnection().SetLearning(target, userTable[0].UserName, userTable[0].Pass, userTable[0].UserID);
Hide();
parent.Populate();
}
else
{
//ask for resubmission with new username
}
}
/// <summary>
/// Updates the activeClientListView predictions for predicting mode clients.
/// </summary>
/// <param name="data">
/// The prediction data from proctor.
/// </param>
public void UpdatePredictions(List <KeyValuePair <UserClient, KeyValuePair <int, double> > > data)
{
if (activeClientsLstView.InvokeRequired)
{
SetPredictionTextCallback d = new SetPredictionTextCallback(UpdatePredictions);
this.Invoke(d, data);
}
else
{
if (activeClientsLstView.Items.Count > 0 && data.Count > 0)
{
foreach (KeyValuePair <UserClient, KeyValuePair <int, double> > prediction in data)
{
UserDBDataSetWorkerTableAdapters.UserClientTableAdapter adapter = new UserDBDataSetWorkerTableAdapters.UserClientTableAdapter();
UserDBDataSetWorker.UserClientDataTable userClientTable = adapter.GetDataByUserID(prediction.Value.Key);
ListViewItem item = activeClientsLstView.Items[prediction.Key.GetName()];
ListViewItem test = activeClientsLstView.Items[0];
item.SubItems[2].Text = userClientTable[0].UserName;
item.SubItems[3].Text = userClientTable[0].UserID.ToString();
item.SubItems[4].Text = (prediction.Value.Value * 100).ToString();
}
}
}
}
private KeyValuePair <int, double> predict(UserClient client)
{
KeyValuePair <int, double> answer;
List <KeyValuePair <int, double> > answerlist = new List <KeyValuePair <int, double> >(), meanAnswerList = new List <KeyValuePair <int, double> >(),
medianAnswerList = new List <KeyValuePair <int, double> >();
double likeness = 0, meanLikeness = 0, medianLikeness = 0;
List <WordData> predictionData = ToWords(client.GetPredictionData());
if (predictionData.Count > 0)
{
UserDBDataSetWorkerTableAdapters.UserClientTableAdapter userAdapt = new UserDBDataSetWorkerTableAdapters.UserClientTableAdapter();
UserDBDataSetWorker.UserClientDataTable userTable = userAdapt.GetUserClientData();
foreach (UserDBDataSetWorker.UserClientRow userRow in userTable)
{
int count = 0;
foreach (WordData word in predictionData)
{
UserDBDataSetWorkerTableAdapters.WordDataTableAdapter wordAdapt = new UserDBDataSetWorkerTableAdapters.WordDataTableAdapter();
UserDBDataSetWorker.WordDataDataTable wordTable = wordAdapt.GetDataByUserIDandWord(userRow.UserID, word.GetWord());
if (wordTable.Count > 0)
{
List <WordData> wordList = new List <WordData>();
foreach (UserDBDataSetWorker.WordDataRow wordRow in wordTable)
{
UserDBDataSetWorkerTableAdapters.TimingTableAdapter timeAdapt = new UserDBDataSetWorkerTableAdapters.TimingTableAdapter();
UserDBDataSetWorker.TimingDataTable timeTable = timeAdapt.GetDataByWordID(wordRow.WordID);
if (timeTable.Count > 0)
{
int[] timing = new int[timeTable.Count];
for (int i = 0; i < timeTable.Count; i++)
{
timing[i] = timeTable[i].Timing;
}
WordData learnedWord = new WordData(wordRow.Word, timing, userRow.UserID);
double comp = Compare(word, learnedWord);
if (comp > 0)
{
likeness += Compare(word, learnedWord);
count++;
}
wordList.Add(learnedWord);
}
}
if (word.GetTiming().Length > 0)
{
meanLikeness = MeanCompare(word, wordList);
medianLikeness = MedianCompare(word, wordList);
}
//meanaverage
}
}
likeness /= count;
answerlist.Add(new KeyValuePair <int, double>(userRow.UserID, likeness));
meanAnswerList.Add(new KeyValuePair <int, double>(userRow.UserID, meanLikeness));
medianAnswerList.Add(new KeyValuePair <int, double>(userRow.UserID, medianLikeness));
meanAList = meanAnswerList;
medianAList = medianAnswerList;
bool problem;
if (likeness > 1)
{
problem = true;
}
likeness = 0;
count = 0;
}
}
if (answerlist.Count > 1)
{
switch (predictionMode)
{
case 0: //compare
answer = MaxValue(answerlist); //most probable prediction
break;
case 1: //mean
answer = MaxValue(meanAnswerList); //most probable prediction
break;
default:
case 2: //median
answer = MaxValue(medianAnswerList); //most probable prediction
break;
}
}
else
{
answer = new KeyValuePair <int, double>(0, 0);
}
return(answer);
}
